Abstract
The application of unmanned aerial vehicles (UAVs) in IoT networks, especially data collection, has received extensive attention. Due to the urgency of the mission and the limitation of the network cost, the number and the mission completion time of UAVs are research hotspots. Most studies mainly focus on the trajectory optimization of the UAV to shorten the mission completion time. However, under different data collection modes, the collection time will also greatly affect the mission completion time. This paper studies the data collection of ground IoT devices (GIDs) in Multi-UAV enabled IoT networks. The problem of data collection is formulated to minimize the number and the maximum mission completion time of UAVs by jointly optimizing the mission allocation of UAVs, hovering location, and the UAV trajectory. In view of the complexity and non-convexity of the formulated problem, we design improved ant colony optimization (IACO) algorithm to determine the number of UAVs by the mission allocation. Then, based on the data collection scheme combining flying mode (FM) and hovering mode (HM), a joint optimization algorithm (JOATC) is proposed to minimize flight time and collection time by optimizing the trajectory of the UAV. Simulation results show that our scheme achieves excellent performance.
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Gao, X., Zhu, X., Zhai, L. (2022). Number of UAVs and Mission Completion Time Minimization in Multi-UAV-Enabled IoT Networks. In: Liu, S., Wei, X. (eds) Network and Parallel Computing. NPC 2022. Lecture Notes in Computer Science, vol 13615. Springer, Cham. https://doi.org/10.1007/978-3-031-21395-3_22
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DOI: https://doi.org/10.1007/978-3-031-21395-3_22
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